Security issues and other motivations for surveillance continue to drive wide scale deployment of systems that can provide monitoring in vehicles, buildings, parking lots and other areas. In some of these systems it is necessary to transmit acquired information to central monitoring locations or to other devices. It is also the case that in some situations, it would be advantageous to have the ability to provide remote monitoring or access to non-party entities. Such non-party entities include law enforcement or emergency service agencies. Current systems are typically closed systems and tend to have proprietary communication schemes and thus provide limited access to data. These closed systems do not lend themselves to scalable widespread deployment or provide the opportunity for open access communication.
Presently, most surveillance systems provide video data and in a few cases, there is also some audio data. However, in certain surveillance or reconnaissance situations, it might be beneficial to obtain other environmental conditions and data, which current systems do not provide. It is thus desirable to have a system that can acquire a wide variety of multi-media and environmental data, and compress such data so that it can be transmitted over a communication channel without requiring a large bandwidth. More specifically, it is desirable to have an audio/video device that incorporates sensors that can monitor and respond to environmental conditions, in order to provide a more complete audio, visual and sensory impression of the device's locale or vicinity.
A great number of currently deployed surveillance systems are primarily based on analog cameras, with more recently deployed systems being based on digital cameras. The analog systems have the draw back of having a resolution that is fixed by the implemented video standard, such as National TV Standards Committee (NTSC)/Phase Alternating Line (PAL)/SEquential Couleur Avec Memoire, Sequential Color with Memory (SECAM). In analog systems, finer details of a scene may be inspected by optical zoom and some form or mechanical tilt and pan of the camera. However, resolution and clarity of images may be lost. As such, digital cameras are being implemented on a wider scale for surveillance systems.
Although existing digital camera based systems addressed the short comings of the analog cameras they also suffer from set backs of their own despite some of the advances that have been made. For example, existing digital cameras, that are network enabled, utilize packet oriented digital image transmission. High resolution video surveillance systems were developed with video rate multi-format functionality and instantaneous pan, tilt and zoom capability. Some digital systems also incorporated image processing capabilities, compression and network transmission. However, these video compression techniques have involved two basic forms of compression processing—spatial and temporal.
Spatial processing compresses information by transforming the picture elements within a particular frame of a video signal in accordance with a compression algorithm, thereby reducing the amount of information required for reproduction of the frame.
Temporal processing incorporates information relating to how information is changing with time. In other words, it reduces the amount of information for picture reproduction of a frame by tracking changes that occur from frame to frame. Specifically, changes are reflected in vectors that are generated and transmitted rather than the actual contents of video frames. More detailed descriptions of spatial and temporal processing can be found in several references within the art.
One compression technique that has been used in the art is the MPEG compression standard, which incorporates both the spatial and temporal processing techniques. However, movement information must be extracted in order to provide motion vectors. The extraction and processing required for conveying information requires relatively large amounts of memory space and computational power. Furthermore, these prior art systems require a balancing of spatial processing against temporal processing in order to accommodate the movement of objects or the camera.
There are existing devices that transmit “live” over the internet or at least reasonably close to real-time. However, the vast majority of devices are not of a commercial grade and thus tend to lack the resolution or refresh rate that would meet the demands of a satisfactory surveillance system. Even further, these devices are not suitable for multiple network deployment and control.
There exists a need for a system that will provide improved data compression and networking capability for surveillance systems without necessitating large memory usage or large computational powers. To further provide flexibility and a more robust system it is desirable to have automated focal point adjustment for the video aspect of the system along with the capability to receive adjustment instructions from other devices on a network. It is further desirable to provide day/night functions so as to yield the best possible images. It is also desirable to include security features to protect the data that is compressed and transferred from the surveillance apparatus.